Description
Summary We're building Ascend, an AI-powered Growth Intelligence platform that leverages multiple specialized AI agents to audit websites, analyze SEO, AEO, content quality, and performance, and generate actionable recommendations. The platform is built around an agentic architecture where independent AI agents collaborate through a central orchestrator to produce comprehensive website audits. We're looking for a senior AI engineer with hands-on experience designing and building production-grade AI systems who can contribute to the architecture and implementation of the platform. Initial Project Scope The first milestone focuses on implementing the Recommendation Agent, one of the core components of the Ascend platform. The Recommendation Agent consumes structured outputs from the Technical SEO, AEO, Content, and Performance agents and produces prioritized, actionable recommendations for the final audit report. Responsibilities Design and implement the Recommendation Agent. Aggregate and reason over outputs from multiple specialized AI agents. Prioritize recommendations based on business impact and implementation effort. Generate structured, deterministic JSON responses suitable for downstream reporting. 1 Expected Output The Recommendation Agent should generate prioritized recommendations including: Priority Expected impact Estimated implementation effort Supporting reasoning Suggested implementation steps Affected pages Requirements 5+ years of software engineering experience. Proven experience building production AI applications. Strong understanding of Agentic AI and multi-agent architectures. Experience with LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks. Experience integrating OpenAI, Anthropic, Gemini, or comparable LLMs. Strong Python and backend development skills. Experience designing structured prompts and JSON-based AI outputs. Familiarity with evaluation, reliability, and production deployment of AI systems. Nice to Have Model Context Protocol (MCP) Knowledge graphs or hybrid retrieval Prompt evaluation and automated testing Docker, Kubernetes, Redis, PostgreSQL Experience deploying AI systems at production scale Budget Fixed Price: $200 USD This milestone represents the first deliverable of the project. Engineers who demonstrate strong technical expertise and code quality will continue working on subsequent modules of the Ascend platform. To Apply Please share: Relevant AI projects GitHub or portfolio A brief overview of your experience with Agentic AI, multi-agent systems, and RAG The AI frameworks you've used in production Produce implementation guidance with supporting reasoning. Build clean, maintainable, production-ready code. Include appropriate testing and documentation. Example Input The agent will receive structured findings from multiple analysis agents, such as: Technical SEO issues AEO findings Content quality analysis Performance metrics